39 citations · 58 across the 6 of their papers we have counts for
4 papers · 1 filter
Self-Supervised Moving Object Segmentation of Sparse and Noisy Radar Point Clouds
Leon Schwarzer, Matthias Zeller, Daniel Casado Herraez +3
Moving object segmentation is a crucial task for safe and reliable autonomous mobile systems like self-driving cars, improving the reliability and robustness of subsequent tasks li…
SemRaFiner: Panoptic Segmentation in Sparse and Noisy Radar Point Clouds
Matthias Zeller, Daniel Casado Herraez, Bengisu Ayan +3
Semantic scene understanding, including the perception and classification of moving agents, is essential to enabling safe and robust driving behaviours of autonomous vehicles. Came…
Radar Velocity Transformer: Single-scan Moving Object Segmentation in Noisy Radar Point Clouds
Matthias Zeller, Vardeep S. Sandhu, Benedikt Mersch +3
The awareness about moving objects in the surroundings of a self-driving vehicle is essential for safe and reliable autonomous navigation. The interpretation of LiDAR and camera da…
Radar Tracker: Moving Instance Tracking in Sparse and Noisy Radar Point Clouds
Matthias Zeller, Daniel Casado Herraez, Jens Behley +2
Robots and autonomous vehicles should be aware of what happens in their surroundings. The segmentation and tracking of moving objects are essential for reliable path planning, incl…